The goal of this project is to investigate the technical feasibility and commercial potential of a platform (PhenoNet) for custom phenotypic data repositories that encourages adoption of phenotypic data standards and exchange of knowledge across sources. Phenotypic data collection today generates large quantities of heterogeneous data and it does not yet match the analogous efforts in genomic research in terms systematization or throughput. Freimer and Sabbati's recently proposed Human Phenome Project will require "an enormous coordinated effort, to obtain phenomic databases that are powerful, standardized, and comprehensive" (2003). PhenoNet will be used by individual investigators or laboratories and will provide users with tools to administer projects, enter data, track progress, and create complex queries. The true significance of the system, however, will be in enabling users to define and map their datasets to accepted standards for phenotypic data, and then share and integrate datasets via these standards. The platform will increase the pace at which research can occur by streamlining the dataset design process, facilitating increased accuracy and throughput in phenotypic data collection, and providing detailed auditing and tracking of the data collection processes. The system will provide an enhanced ability to store, manipulate, and share phenotypic data. An adjunct PhenoNet "Registry" will serve as a centralized directory of investigators with standards compliant datasets, enabling researchers to find collaborators and integrate disparate data based on common mapping to accepted standards. In doing so, PhenoNet will allow for novel research designs by facilitating data mining of detailed phenotypic datasets in ways that are currently prohibitively complex. By examining data in these new ways, investigators will be able to produce more granular characterizations of expressed traits that can lead to more effective analysis when studying genetic or environmental influences on disease as well as refinement and better understanding of disease phenotypes. Phase I will include analysis and design of all major components of the system as well as construction and evaluation of a prototype system in the field of psychiatric and neurological research.